The present invention relates to a method of and system for evaluating and assessing the quality of contacts stored in a data source. Some specific embodiments of the invention are particularly useful for ranking sales leads according to rules defined by a user intending to identify leads that are more likely than other to produce possible sales.
Information drives corporate marketing and sales programs, which in turn drive organizations. Most organizations have built large customer databases to track and drive these activities through consolidation of data from heterogeneous sources. Unfortunately, these customer lists are typically generated from heterogeneous data sources of varying quality. The quality varies for a number of reasons: sources do not always provide the same data attributes; data timeliness is not guaranteed; and those who entered the data may have had no incentive to provide quality data (e.g. an online survey participant). Thus, entries in the data source are often incomplete and/or inaccurate.
Traditionally, the customer lists are generated and filtered using various ad-hoc methods, such as database queries. For example, in some organizations the customer list is provided to sales managers, who often manually filter poor quality leads and prioritize the leads based on personal experience and intuition. Sales organizations have a different perspective on quality of data than marketing organizations. Apart from the direct impact on revenue, poor quality data may also foster mistrust between sales and marketing organizations.
Accordingly, it can be appreciated that improved methods of assessing the quality of, sorting and filtering sales leads, or other contact information for that matter, are desirable.